Instructions to use nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("katuni4ka/tiny-random-falcon-40b") model = PeftModel.from_pretrained(base_model, "nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56: direct link, hf CLI and curl.
- Browser
- Download file 129 kB
-
https://huggingface.co/nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56/resolve/85d892320fdda41c0e1f82e1d193ab03747d2370/adapter_model.bin
- Command line
-
hf download hf://nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56@85d892320fdda41c0e1f82e1d193ab03747d2370/adapter_model.bin
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curl -L -o adapter_model.bin https://huggingface.co/nblinh63/127670ad-3792-44a9-ba8e-1f0437b51b56/resolve/85d892320fdda41c0e1f82e1d193ab03747d2370/adapter_model.bin
129 kB
- Xet hash:
- 683644a795fb2a1abe98736879855694b0ac7f9127f38b2bee4e264d2dbf051e
- Size of remote file:
- 129 kB
- SHA256:
- 6f4a83ff8ccd9db771d48204df81638596524528c4afb23c713fa234802fadbc
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